DBMS > Apache Drill vs. Heroic vs. Machbase Neo vs. Teradata

System Properties Comparison Apache Drill vs. Heroic vs. Machbase Neo vs. Teradata

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

TimeSeries DBMS for AIoT and BigData

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

drill.apache.org

github.com/spotify/heroic

machbase.com

www.teradata.com

Technical documentation

drill.apache.org/docs

spotify.github.io/heroic

machbase.com/dbms

docs.teradata.com

Developer

Apache Software Foundation

Spotify

Machbase

Teradata

Initial release

2012

2014

2013

1984

Current release

1.20.3, January 2023

V8.0, August 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

commercial

free test version available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

hosted
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

via Elasticsearch

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C++

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

volatile and lookup table

yes

User concepts

Access control

Depending on the underlying data source

simple password-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

show all

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

마크베이스, 개발 생산성 최대 90%↑…신개념 DB 'MACHBASE NEO 8.0' 출시
4 September 2023, 전자신문

[IoT 데이터 처리의 모든 것-②] IoT 데이터 전쟁의 서막
6 October 2021, 헬로티 – 매일 만나는 첨단 산업, IT 소식

마크베이스, 오픈소스 에디션 'MACHBASE NEO' 출시
28 March 2023, 전자신문

IoT 데이터 최적화 '시계열 데이터베이스' 등장
15 September 2019, 데이터넷

provided by Google News

Truist Financial Corp Reduces Position in Teradata Co. (NYSE:TDC)
19 May 2024, Defense World

Bear of the Day: Teradata (TDC)
17 May 2024, Yahoo Singapore News

Teradata Stockholders Approve Incentive Plan and Elect Directors - TipRanks.com
17 May 2024, TipRanks

An interview with Teradata CFO Claire Bramley
9 February 2024, McKinsey

Lakehouse dam breaks after departure of long-time Teradata CTO
1 May 2024, The Register

provided by Google News

Share this page